Multi-Time Scale Optimal Operation of Integrated Energy Station Combined With Electricity-Heat-Hydrogen Energy Storage

Jiaqi YANG; Shunyu ZHANG; Sa GAO; Binbin SHAN; Shaokun WANG; Aihua NING; Zhenling ZHOU; Xiangrui MENG; Di WU; Guangya JIN

doi:10.16513/j.2096-2185.DE.2409206

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Distributed Energy ›› 2024, Vol. 9 ›› Issue (2) : 48-62. DOI: 10.16513/j.2096-2185.DE.2409206

Basic Research

Multi-Time Scale Optimal Operation of Integrated Energy Station Combined With Electricity-Heat-Hydrogen Energy Storage

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Abstract

Multi-energy storage is an effective way to improve the renewable energy consumption level of integrated energy system. However, with the increase of coupled energy storage equipment, the complexity of the system increases. Unstable operation and low energy efficiency caused by the complexity and uncertainty of the system have restricted the development of integrated energy system. Therefore, this paper proposes to integrate electricity storage, heat storage and hydrogen storage into the integrated energy system, and researches on multi-timescale optimization. From the construction of the system model to proposing multi-timescale optimization schemes such as day-ahead optimal scheduling, intra-day rolling optimization, and real-time adjustment, the advantages of multi-energy storage are fully utilized to solve the impact of source-load uncertainty on the system. The results show that the total power storage is adjusted to 12.421 99 MW unbalanced power, the community renewable energy consumption level is increased by 0.42%, the electricity purchase cost is reduced by 3.5%, and the carbon tax is reduced by 1.5%. This shows that the proposed multi-timescale optimal operation method makes the system run more smoothly by flexibly adjusting the output of each device, and improves the stability of the system and the level of renewable energy consumption.

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multi-energy storage / multi-timescale / integrated energy system / operation optimization

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Jiaqi YANG , Shunyu ZHANG , Sa GAO , et al . Multi-Time Scale Optimal Operation of Integrated Energy Station Combined With Electricity-Heat-Hydrogen Energy Storage[J]. Distributed Energy Resources. 2024, 9(2): 48-62 https://doi.org/10.16513/j.2096-2185.DE.2409206

References

List( Publishing order | Descend order by publishing year | Descend order by cited within ) Chart analysis

[1]	International Renewable Energy Agency. Global renewables outlook: Energy transformation 2050[EB/OL]. (2020-08-01)[2023-02-02]. https://www.irena.org/Publications/2020/Apr/Global-Renewables-Outlook-2020 Cited in this article [1]

[2]	中国建筑节能协会，2022年度中国城乡建设领域碳排放系列研究报告[EB/OL]. (2023-01-04)[2023-02-02]. https://www.cabee.org/site/content/24420.html Cited in this article [1]

[3]	REN H, JIANG Z, WU Q, et al. Integrated optimization of a regional integrated energy system with thermal energy storage considering both resilience and reliability[J]. Energy, 2022, 261: 125333. Cited in this article [1]

[4]	杨滢，杨晓雷，项中明，等. 参与一次调频储能型风电场的交流外送振荡特性分析[J]. 智慧电力，2023, 51(9): 105-112. YANG Ying, YANG Xiaolei, XIANG Zhongming, et al. Oscillation characteristic analysis of wind farm with energy storage participating primary frequency control[J]. Smart Power, 2023, 51(9): 105-112. Cited in this article [1]

[5]	傅旭，王莹玉，张雨津. 新疆电网调峰需求及储能电源配置[J]. 分布式能源，2022, 7(5): 63-68. FU Xu, WANG Yingyu, ZHANG Yujin. Peak regulating demand and energy storage power supply configuration of Xinjiang power grid[J]. Distributed Energy, 2022, 7(5): 63-68. Cited in this article [1]

[6]	ZHAO D, XIA Z, GUO M, et al. Capacity optimization and energy dispatch strategy of hybrid energy storage system based on proton exchange membrane electrolyzer cell[J]. Energy Conversion and Management, 2022, 272: 116366. Cited in this article [1]

[7]

王成山，吕超贤，李鹏，等. 园区型综合能源系统多时间尺度模型预测优化调度[J]. 中国电机工程学报，2019, 39(23): 6791-6803, 7093.

WANG

Chengshan

, LÜ

Chaoxian

, LI

Peng

, et al. Multiple time-scale optimal scheduling of community integrated energy system based on model predictive control[J]. Proceedings of the CSEE, 2019, 39(23): 6791-6803, 7093.

Cited in this article [1]

[8]	汤翔鹰，胡炎，耿琪，等. 考虑多能灵活性的综合能源系统多时间尺度优化调度[J]. 电力系统自动化，2021, 45(4): 81-90. TANG Xiangying, HU Yan, GENG Qi, et al. Multi-time-scale optimal scheduling of integrated energy system considering multi-energy flexibility[J]. Automation of Electric Power Systems, 2021, 45(4): 81-90. Cited in this article [1]

[9]	徐健玮，马刚，高丛，等. 基于风光场景生成的综合能源系统日前-日内优化调度[J]. 分布式能源，2022, 7(4): 18-27. XU Jianwei, MA Gang, GAO Cong, et al. Day-ahead and intra day optimal scheduling of integrated energy systems based on scenario generation[J]. Distributed Energy, 2022, 7(4): 18-27. Cited in this article [1]

[10]	FANG X, DONG W, WANG Y, et al. Multiple time-scale energy management strategy for a hydrogen-based multi-energy microgrid[J]. Applied Energy, 2022, 328: 120195. Cited in this article [1]

[11]	JANI A, KARIMI H, JADID S. Multi-time scale energy management of multi-microgrid systems considering energy storage systems: A multi-objective two-stage optimization framework[J]. Journal of Energy Storage, 2022, 51: 104554. Cited in this article [1]

[12]	LI P, WANG Z, WANG J, et al. A multi-time-space scale optimal operation strategy for a distributed integrated energy system[J]. Applied Energy, 2021, 289: 116698 Cited in this article [2]

[13]	LIU H, ZHAO X, LI G, et al. Investigation of a novel separately-configured micro-thermoelectric cooler to enabling extend application scope[J]. Applied Energy, 2022, 306: 117941. Cited in this article [1]

[14]	GABRIELLI P, GAZZANI M, MAZZOTTO M. Electrochemical conversion technologies for optimal design of decentralized multi-energy systems: Modeling framework and technology assessment[J]. Applied Energy, 2018, 221: 557-575. Cited in this article [1]

[15]	LI B, ROCHE R, PAIRE D, et al. Sizing of a stand-alone microgrid considering electric power, cooling/heating, hydrogen loads and hydrogen storage degradation[J]. Applied Energy, 2017, 205: 1244-1259. Cited in this article [1]

[16]	E J, ZHANG B, ZENG Y, et al. Effects analysis on active equalization control of lithium-ion batteries based on intelligent estimation of the state-of-charge[J]. Energy, 2022, 238: 121822. Cited in this article [2]

[17]	LI B, MIAO H, LI J. Multiple hydrogen-based hybrid storage systems operation for microgrids: A combined TOPSIS and model predictive control methodology[J]. Applied Energy, 2021, 283: 116303. Cited in this article [1]

[18]	LI H, ZHANG C, SUN B. Optimal design for component capacity of integrated energy system based on the active dispatch mode of multiple energy storages[J]. Energy, 2021, 227: 120522 Cited in this article [1]

[19]	YANG H, LI M, JIANG Z, et al. Multi-time scale optimal scheduling of regional integrated energy systems considering integrated demand response[J]. IEEE Access, 2020, 8: 5080-5090. Cited in this article [1]

[20]	LI P, ZHANG F, MA X, et al. Multi-time scale economic optimization dispatch of the park integrated energy system[J]. Frontiers in Energy Research, 2021, 9: 743619. Cited in this article [1]

[21]	PU Y, LI Q, ZOU X, et al. Optimal sizing for an integrated energy system considering degradation and seasonal hydrogen storage[J]. Applied Energy, 2021, 302: 117542. Cited in this article [1]

[22]	WEN X, SUN B, GU B, et al. Multi-time scale optimal scheduling model of wind and hydrogen integrated energy system based on carbon trading[J]. Processes, 2023, 11(2): 344. Cited in this article [2]

[23]	CHENG Z, JIA D, LI Z, et al. Multi-time scale dynamic robust optimal scheduling of CCHP microgrid based on rolling optimization[J]. International Journal of Electrical Power & Energy Systems, 2022, 139: 107957. Cited in this article [1]

[24]	WANG Z, TAO H, CAI W, et al. Study on the multitime scale rolling optimization operation of a near-zero energy building energy supply system[J]. Energy Conversion and Management, 2022, 270: 116255. Cited in this article [1]